Md F.

Key Skills

Software

Don't disclose

Other

Top Subject Matter

Software development workflows and professional engineering practices.

Algorithm practice for AI training preparedness (programming/data processing).

Cybersecurity training via guided labs (threat-awareness and offensive-security fundamentals).

Top Data Types

Text

Image

Document

Top Task Types

Data Collection

Red Teaming

Freelancer Overview

Industrial Attachment Trainee (software-industry exposure). Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose and Other. Education includes Bachelor of Science in Computer Science and Engineering, Bangladesh Army University of Engineering and Technology (2026) and Higher Secondary Certificate, Adamjee Cantonment College (2021). AI-training focus includes data types such as Computer Code, Programming, and Text and labeling workflows including Computer Programming, Coding, and Data Collection.

Labeling Experience

Cybersecurity Learner (TryHackMe)

OtherTextRed Teaming

Completed and is currently progressing through guided cybersecurity learning paths and hands-on offensive-security labs. The training emphasizes building practical familiarity with reconnaissance workflows, Linux basics, and network/web security concepts. The experience supports skills used in threat detection and AI-assisted security labeling tasks, even though specific labeling artifacts are not explicitly stated. • Followed guided rooms and learning paths for cybersecurity fundamentals. • Practiced reconnaissance and threat-awareness workflows. • Focused on Linux basics and network/web security concepts. • Improved practical security skills through lab-based guided training.

2026 - Present

Active Problem Solver (LeetCode)

OtherData Collection

Actively solved 850+ LeetCode programming problems to strengthen algorithmic and analytical skills that are frequently used in AI training and data-processing pipelines. This involved repeated practice across core programming patterns such as recursion, sorting/searching, and dynamic programming. The experience reflects continuous hands-on technical training aligned with building and evaluating computational models. • Trained on arrays, strings, recursion, sorting, searching, and dynamic programming. • Worked with graphs and performed time/space complexity analysis. • Used competitive problem-solving to improve optimization reasoning. • Sustained ongoing practice as an ongoing learning activity.

2026 - Present

Industrial Attachment Trainee (software-industry exposure)

Don't disclose

Completed an industrial attachment focused on real-world software workflows, team communication, and structured engineering practices. While not described as direct data labeling, the role included exposure to how engineering teams document and collaborate on production processes. This experience supported readiness to participate in data-labeling or AI-training workflows where quality and process discipline matter. • Supported software development life cycle understanding and workplace discipline. • Practiced professional communication and documentation habits in a corporate environment. • Gained adaptability through learning technical concepts in a structured setting. • Improved readiness for AI/data-training task execution through engineering process exposure.

2025 - 2026

Education

Work History